Demographic Inference and Representative Population Estimates from Multilingual Social Media Data

Social media provide access to behavioural data at an unprecedented scale and granularity. However, using these data to understand phenomena in a broader population is difficult due to their non-representativeness and the bias of statistical inference tools towards dominant languages and groups. While demographic attribute inference could be used to mitigate such bias, current techniques are almost entirely monolingual and fail to work in a global environment. We address these challenges by combining multilingual demographic inference with post-stratification to create a more representative population sample. To learn demographic attributes, we create a new multimodal deep neural architecture for joint classification of age, gender, and organization-status of social media users that operates in 32 languages. This method substantially outperforms current state of the art while also reducing algorithmic bias. To correct for sampling biases, we propose fully interpretable multilevel regression methods that estimate inclusion probabilities from inferred joint population counts and ground-truth population counts. In a large experiment over multilingual heterogeneous European regions, we show that our demographic inference and bias correction together allow for more accurate estimates of populations and make a significant step towards representative social sensing in downstream applications with multilingual social media.Comment: 12 pages, 10 figures, Proceedings of the 2019 World Wide Web Conference (WWW '19

The Russian detour : real transition in a virtual economy?

Illustrates the creation of a market economy by showing that no easy procedures automatically lead to that goal; the Russian forest sector is used as a model for all Russian industries. The major obstacle for the forest sector is the existing institutional framework consisting of both formal & informal rules. In Russia, the institutional system adversely affects the new & more market-oriented institutions. Indeed, multiple problems undermine the Russian forest industry. Laws are often ignored, property rights are ill defined, the market does not always determine value, & authorities often fail to prosecute violations of laws. Through a comparative study of the Russian & Swedish forest industries the authors reveal that Russian firms lack funding & bank support, they are more burdened by taxes, & trading is marred by contract violations. Further complicating the issue is Russia's overlapping jurisdictions; the forest sector is regulated by three levels of rules. Consequently, the problems must be solved at three different levelsValiderad; 2001; 20070207 (keni

Consumer Xenocentrism as Determinant of Foreign Product Preference: A System Justification Perspective

Foreign and domestic product purchase behavior largely depends on consumer predispositions. The dominant construct in international marketing literature explaining such behavior has been consumer ethnocentrism, which is conceptually anchored in social identity theory. However, such a perspective overlooks evidence that certain consumers are consistently attracted by the “foreignness” of a product. Drawing from system justification theory, the present investigation conceptualizes and provides an empirical test of the consumer xenocentrism construct that is intended to explain consumer attraction toward foreign products. Using survey data from five complementary studies, the authors develop and validate a new scale (the C-XENSCALE) to measure consumers’ xenocentric tendencies and offer extensive evidence on its ability to explain consumer preferences for foreign products. The authors discuss implications of the findings for theory and managerial practice and identify future research directions